MR molecular imaging of early endothelial activation in focal ischemia
Bibliographic record
Abstract
Focal ischemia followed by reperfusion initiates a harmful P- and E-selectin-mediated recruitment of leukocytes in brain microvasculature. In this study, we tested whether a novel magnetic resonance (MR) contrast agent (Gd-DTPA-sLe(x) A), which is designed to bind to activated endothelium could be detected by MR imaging (MRI) in a focal stroke mouse model. MRIs (9.4T) of the brain were acquired 24 hours after transient middle cerebral artery occlusion. T1 maps were acquired repeatedly before and up to 1.5 hours after the intravenous injection of either Gd-DTPA or Gd-DTPA-sLe(x) A. Analysis of images included a pixel-by-pixel subtraction of T1 maps from the precontrast T1 maps and quantification of T1 within the ischemic area. After injection of Gd-DTPA-sLe(x) A, T1 decreased compared with precontrast levels, and an interhemispheric difference between the pre-post contrast T1 developed within the stroke lesion at a mean time of 52 minutes after injection (p < 0.05). Animals injected with Gd-DTPA did not exhibit changes in T1 signal intensity between regions of the ipsilateral and contralateral hemispheres, indicating that the reductions in T1 observed with Gd-DTPA-sLe(x) A were unrelated to blood-brain barrier breakdown. Fluorescent-labeled sLe(x) A administered intravenously was observed to bind to the endothelium of injured but not control brain. The study suggests that the contrast agent Gd-DTPA-sLe(x) A can be used to visualize early endothelial activation after transient focal ischemia in vivo with MRI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".